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22 Feb 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique de l'ENS Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage Researcher
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for the Advancement of Surgery) initiative. The Research Associate will be responsible for developing machine learning algorithms and creating predictive models. The ideal candidate must demonstrate a robust background
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. Cleaning, structuring, and annotating the data needed to train and validate AI models. Development of AI modules and alert systems: Development and integration of algorithms for analysis, anomaly detection
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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work
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environments (preferred). You possess the ability to conduct independent research and develop novel algorithms. You have strong analytical and problem-solving skills. You have a research-oriented mindset and
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. Responsibilities Application of Domain Expertise: Maintain strong command of AI and machine learning concepts, including underlying science, math, and algorithms; stay current through reading publications, reviewing
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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oversee and develop algorithms for analyzing ensemble genomics data, single cell genomics data, single cell merFISH and sequential oligopaints imaging data, as well as novel molecular connectomics data
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/adaptive algorithms, offline and online data analysis, conducting experimental research, and online evaluation of the developed adaptive strategies with a robotic application. The prospective students can
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with benefits. Qualifications Ability to create and use statistical algorithms to answer complex research questions. (Required) Expertise in statistical analyses including generalized linear model